code: def split_dataset(dataset, test_ratio=0.30):
      """
      Splits a panda dataframe in two, usually for train/test sets.
      Using the same random seed ensures we get the same split so
      that the description in this tutorial line up with generated images.
      """
      test_indices = np.random.rand(len(dataset)) < test_ratio
      return dataset[~test_indices], dataset[test_indices]
  
file_path: dtreeviz/testing/tf-catvars.py
imports: import tensorflow_decision_forests
  import dtreeviz
  import tensorflow
  import os
  import numpy
  import pandas
  import tensorflow
  import math
  from matplotlib import pyplot
label_desc: Use image node_id 1 for calling a global function with example usage: split_dataset(dataset, test_ratio) and returns: dataset,  dataset